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Abstract

Over the past few decades, cardiovascular diseases have surpassed all other causes of death as the main killers in industrialised, underdeveloped, and developing nations. Early detection of heart conditions and clinical care can lower the death rate. Based on the patient's various cardiac features, we proposed a model for forecasting heart disease and identifying impending heart disease using machine learning techniques In most cases,input is received through numerical data of various parameters, and output findings are generated in real-time, predicting whether or notthe patient has a disease. Well use a variety of supervised machine learning methods before deciding which one is best for the model. Existing systems rely on classical deep learning models, which are inefficient and imprecise. They aren't as accurate as the proposed model and take a little longer to process.

Details

1009240
Title
A NOVEL CORONARY HEART STROKE PREDICTION SYSTEM USING MACHINE LEARNING TECHNIQUES
Author
Balaji, A 1 ; Bhargavi, Chigurupati 2 ; Vasavi, Makkena 2 ; Bhargavi, Vallala 3 ; Raghavendra, Potharlanka Kumara Venkata Sai 2 

 Department of Computer Science Engineering, Chalapathi Institute of Engineering and Technology, LAM, Guntur, Andhra Pradesh, India 
 Department of CSE & AI, Chalapathi Institute of Engineering and Technology, LAM, Guntur, Andhra Pradesh, India 
 Department of CSE & AI,Chalapathi Institute of Engineering and Technology, LAM, Guntur, Andhra Pradesh, India 
Volume
15
Issue
1
Pages
91-95
Publication year
2024
Publication date
2024
Section
Research Article
Publisher
Ninety Nine Publication
Place of publication
Gurgaon
Country of publication
India
Publication subject
e-ISSN
13094653
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
ProQuest document ID
3065454620
Document URL
https://www.proquest.com/scholarly-journals/novel-coronary-heart-stroke-prediction-system/docview/3065454620/se-2?accountid=208611
Copyright
© 2024. This work is published under https://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-07-15
Database
ProQuest One Academic